Social Inclusion in the World of Modern Predictive Analytics

Social Inclusion in the World of Modern Predictive Analytics

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The volume of digital data is increasing by around 61 % annually. The rapidly developing techniques of predictive analytics make it possible to use this data in underwriting and pricing of insurers. These novel technologies present huge opportunities for societies to utilize pooling of risks better and better. For insurers better techniques help not only to cover risks more efficiently but also to better manage adverse selection and moral hazard, and also to combat insurance fraud. With these benefits we also have threats. Does increasingly exact risk-based underwriting lead to a decrease in the inherent solidarity, existing not only in mandatory or social insurance but also in voluntary insurance? Do we end up in a situation where lack of insurance leads to a larger part of the population being socially excluded (recognizing that modern techniques, when used responsibly, can also reduce exclusion)? The paper looks at the problem of avoiding social exclusion in the context of evolving techniques. It is connected to the thinking of the Consultative Expert Group on Digital Ethics set up by EIOPA, where the author is chairing one of the three workstreams.

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